Instructions to use prajjwal1/bert-tiny-mnli with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use prajjwal1/bert-tiny-mnli with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("text-classification", model="prajjwal1/bert-tiny-mnli")# Load model directly from transformers import AutoTokenizer, AutoModelForSequenceClassification tokenizer = AutoTokenizer.from_pretrained("prajjwal1/bert-tiny-mnli") model = AutoModelForSequenceClassification.from_pretrained("prajjwal1/bert-tiny-mnli") - Notebooks
- Google Colab
- Kaggle
Commit ·
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Parent(s): b6d720b
upload flax model
Browse files- flax_model.msgpack +3 -0
flax_model.msgpack
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version https://git-lfs.github.com/spec/v1
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oid sha256:6acc54f7396e02e5b3221253a7898cac7a4ce6082be5b03558423889f0c878e4
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size 17546715
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